Fluorine-labelled proteins for NMR spectroscopy. The technique developed in this project has direct impact on pharmaceutical research: NMR spectroscopy is used routinely to identify chemical compounds that bind to protein targets. This project includes the development of novel assignment techniques of 19F-labelled proteins, so that 19F-NMR can be used to detect specific binding interactions. One of the methods proposed here is designed to reveal structural information about the binding mode in s ....Fluorine-labelled proteins for NMR spectroscopy. The technique developed in this project has direct impact on pharmaceutical research: NMR spectroscopy is used routinely to identify chemical compounds that bind to protein targets. This project includes the development of novel assignment techniques of 19F-labelled proteins, so that 19F-NMR can be used to detect specific binding interactions. One of the methods proposed here is designed to reveal structural information about the binding mode in solution with atomic detail. This knowledge can significantly accelerate drug development. It is otherwise only available from crystal structures that can not always be determined.Read moreRead less
Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering ap ....Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering applications which will both reduced the bandwidth required and make the internet safer for users. Finally, it will enable rapid deployment of sensor networks for monitoring and detection, such as for environmental monitoring and safeguarding Australia's borders.Read moreRead less
Computer Vision Optimization Problems Using Machine Learning. Computer Vision concerns itself with understanding the world through the analysis of images obtained by a video or still camera. An important application is tracking of people in video and modelling their movements. This has evident applications in security, sport and entertainment. By enabling the computer to capture the motion of a subject in a video, we may detect suspicious activity in security, analyze the motion (golf-swing, ....Computer Vision Optimization Problems Using Machine Learning. Computer Vision concerns itself with understanding the world through the analysis of images obtained by a video or still camera. An important application is tracking of people in video and modelling their movements. This has evident applications in security, sport and entertainment. By enabling the computer to capture the motion of a subject in a video, we may detect suspicious activity in security, analyze the motion (golf-swing, diving style) of a sports-person, or capture the motion of an actor for animation or game applications. Development of a reliable technology requires new optimization techniques, which will place Australia at the forefront of the application of such research, commercially and for the public benefit.Read moreRead less
Optimisation of piezoelectric metamaterials: Towards robotic stress sensors. This project aims to design new piezoelectric material microstructures that can enhance the measurement of complex local stress states within robotic limbs. The project expects to generate new knowledge of the achievable properties of multi-poled piezoelectric materials and develop computational tools for the analysis and structural optimisation of such materials. The designed microstructures may revolutionise piezoelec ....Optimisation of piezoelectric metamaterials: Towards robotic stress sensors. This project aims to design new piezoelectric material microstructures that can enhance the measurement of complex local stress states within robotic limbs. The project expects to generate new knowledge of the achievable properties of multi-poled piezoelectric materials and develop computational tools for the analysis and structural optimisation of such materials. The designed microstructures may revolutionise piezoelectric sensor technology. Expected outcomes include manufactured proof-of-concept sensors that enable measurement of local stress fields. This should provide significant benefits, such as improved future robot capability and reliability, and research training for next-generation Australian computational mathematicians. Read moreRead less
Frontiers in inference about risk. The project aims to develop new methods for robust risk evaluation and minimisation under various constraints and scenarios. Risk evaluation, estimation and prediction using past data is a central activity in diverse areas such as finance, insurance, superannuation and environmental regulation. The project aims to propose and solve innovatively robust risk optimisation problems under constraints, taking into account the time dynamics. Applications include risk ....Frontiers in inference about risk. The project aims to develop new methods for robust risk evaluation and minimisation under various constraints and scenarios. Risk evaluation, estimation and prediction using past data is a central activity in diverse areas such as finance, insurance, superannuation and environmental regulation. The project aims to propose and solve innovatively robust risk optimisation problems under constraints, taking into account the time dynamics. Applications include risk management around natural catastrophes and long-term asset investment of pension funds. The solutions and outcomes are expected to deliver optimal resource allocation proposals and better management of risk exposure in practice.Read moreRead less
Data Adaptive Geophysical Inversion. The goal of this project is to develop new techniques for extracting information about the interior structure of the Earth from large geophysical data sets. These methods will be adaptive so that they allow the definition of the physical model to be constrained by the character of the data. The project will utilize advances in computational geometry, nonlinear inversion and interactive computer visualisation to extract robust information from data sets with v ....Data Adaptive Geophysical Inversion. The goal of this project is to develop new techniques for extracting information about the interior structure of the Earth from large geophysical data sets. These methods will be adaptive so that they allow the definition of the physical model to be constrained by the character of the data. The project will utilize advances in computational geometry, nonlinear inversion and interactive computer visualisation to extract robust information from data sets with variable resolving power. The resulting algorithms will be applicable to a wide range of problems in the physical sciences.Read moreRead less
Intriguing aerodynamics of bees, hoverflies and beyond. Nature observers have long been fascinated by the elegance, agility and endurance of flying insects, but still human-engineered vehicles fail to match their performance. This project aims to reveal the key physical aspects that allow two different insects to fly so well and thus unlock greater performance for flapping flight vehicles beyond insects.
Unifying Modern Approaches in Machine Learning. The proposed research will lead to better algorithms for some important machine learning problems that could lead to better tools for extracting useful knowledge from data such as in bioinformatics and sensor networks; it will strengthen an international collaboration with one of the world's top centres of machine learning research; it will contribute to an open source toolkit of machine learning algorithms which will put Australia on the map as a ....Unifying Modern Approaches in Machine Learning. The proposed research will lead to better algorithms for some important machine learning problems that could lead to better tools for extracting useful knowledge from data such as in bioinformatics and sensor networks; it will strengthen an international collaboration with one of the world's top centres of machine learning research; it will contribute to an open source toolkit of machine learning algorithms which will put Australia on the map as a provider of sophisticated machine learning software; it will provide training opportunities for several PhD students and a postdoc to work with some of the best machine learning researchers in the world.Read moreRead less
Numerical Algorithms for Solving Convex Optimization Problems Arising in Systems and Control Theory. The need to optimize occurs frequently in engineering applications. Typically one has a set of constraints specifying what solutions are allowable or meet design specifications and one would like to choose from these allowable solutions one which is optimal with respect to some meaningful metric. Such optimization problems tend to be rather complicated and must be solved numerically. This project ....Numerical Algorithms for Solving Convex Optimization Problems Arising in Systems and Control Theory. The need to optimize occurs frequently in engineering applications. Typically one has a set of constraints specifying what solutions are allowable or meet design specifications and one would like to choose from these allowable solutions one which is optimal with respect to some meaningful metric. Such optimization problems tend to be rather complicated and must be solved numerically. This project is concerned with creating improved numerical algorithms for solving particular important classes of optimization problems that arise in systems and control theory.Read moreRead less
Researching the Social Role of Religions in Australia. Most Australians claim allegiance to various religions in the Census. The number of religious denominations has greatly increased in recent years, most notably through immigration, with significant numbers from all world religions. Political and social policies are frequently influenced by religious principles and a detailed analysis of this variety is of crucial national importance. Religions from neighbouring societies are significantly r ....Researching the Social Role of Religions in Australia. Most Australians claim allegiance to various religions in the Census. The number of religious denominations has greatly increased in recent years, most notably through immigration, with significant numbers from all world religions. Political and social policies are frequently influenced by religious principles and a detailed analysis of this variety is of crucial national importance. Religions from neighbouring societies are significantly represented in Australia. Understanding them is of central importance in international political and commercial activity. Current research is essential, based on the most recent Census and other recent socio-economic information.
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